Due to the flexibility obtained through both materials and structures, soft robots have wide potential applications in complicated internal and external environments. This paper presents a new soft crawling robot with multiple locomotion patterns that integrate inchworm motion and various turning motions. First, the conceptual design of the proposed robot is presented by introducing thick-panel origami into the synthesis of a crawling robot, resulting in a Waterbomb-structure-inspired hybrid mechanism. Second, all locomotion patterns of the robot are precisely described and analyzed by screw theory in an algebraic manner, which include inchworm motion, restricted planar motion, quantitative turning motion, and marginal exploration motion. Then, the output motion parameter for each locomotion pattern is analytically modeled as a function of the robotic dimensional parameters, and the robot can thus be designed and controlled in a customized way for the expected output motion. Finally, the theoretical analysis and derivations are validated by simulation and physical prototype building, which lay the foundations for the design and manufacture of small-scale soft crawling robots with precise output motions in a complex planar environment.

At present, the research of soft crawling robot pays more attention to the material manufacturing, but neglects the robot modeling. The high degree of freedom of the soft crawling robot makes it more difficult to establish its motion model and analyzes its motion performance. The centimeter-level wireless driven soft crawling robot has great advantages and application scenarios in narrow space exploration. Therefore, this paper proposed a soft robot driven by magnetism to crawling inchworm. By studying the crawling behavior of inchworm and the characteristics of flexible materials driven by magnetism, the structure of the soft robot was designed and the motion model of inchworm was established. The motion model is analyzed and simulated, the structure size of the robot is optimized, and the effectiveness of the model is verified by experiments. The robot’s crawling motion is realized by coupling the structure of the robot’s torso and legs with the flexible magnetic film. Driven by the alternating magnetic field, the maximum motion speed of the robot is 28.24 mm/s. At the same time, the robot can also move in narrow space such as pipes, which can satisfy the centimeter-level space detection and ensure the high efficiency, providing a new idea for narrow space detection.

Fiber winding reinforcement is widely used in soft robotic manipulators actuated by pressurized fluids. However, the specific effect of each type of winding on the bending motion of a tubular soft robotics manipulator with three chambers has not been explored widely. We present the development of precise finite element (FE) simulations and investigate the effect of helical fiber winding parameters on the bending motion of a two-degree-of-freedom manipulator with three internal chambers. We first show the development of an FE simulation that optimizes convergence and computational time and precisely matches the behavior of soft robots in practice. Compared to single-chamber robots, simulating three-chamber designs is more challenging due to the complex geometry. We then apply our FE model to simulate all the parameter variations. We show that for helical winding with a constant pitch, the closer the center of a chamber is to the intersection of the windings, the lower the bending stiffness of the chamber is. To minimize bending stiffness variation in different bending directions, the optimal angle between the center of the first chamber and the intersection of the two helical windings are 0° and 12°. Reducing the pitch of the helical windings or using other types of windings (i.e., ring winding or six helical winding) reduces the stiffness variation across different bending directions. The FE simulations are compared with experiments showing that the model can capture complex bending behaviors of the manipulator, even though the estimation tends to be less accurate at higher bending angles.

In the paper, a novel modular soft robot that can crawl and turn is presented. The modular soft robot is composed of multiple drive modules connected in series, including one head module, one tail module and three body modules. Each module is actuated by the air chamber. Due to the nonlinear performance of the air chamber, the strain energy function of the air chamber is established. The relationship between the displacement of the air chamber expansion wall and the inflation pressure is obtained, and the manufacturing parameters of the air chamber are determined. By dividing the body of the robot into a series of continuous flexible models, the driving force and the friction force of the robot in locomotion are analyzed. An inflation and deflation control method is presented to complete the locomotion. According to the experiment, the crawling speed of the robot can reach 15.53 mm/s (0.03 body length per second). The turning speed of the robot can reach 1.273 °/s. The robot can crawl and turn on the rough blanket surface effectively. The robot can explore and move in a complex and changeable environment.

The aim of this work is to design and model a novel modular bionic soft robot for crawling and crossing obstacles. The modular bionic soft robot is composed of several serial driving soft modules, each module is composed of two parallel soft actuators. By analyzing the influence of working pressure and manufacturing size on the stiffness of the modular bionic soft robot, the nonlinear variable stiffness model of the modular bionic soft robot is established. Based on this model, the spatial states and design parameters of the modular bionic soft robot are discussed when the modular bionic soft robot can pass through the obstacle. Experiments show that when the inflation air pressure of the modular bionic soft robot is 70 kPa, its speed can reach 7.89 mm/s and the height of obstacles passed by it can reach 42.8 mm. The feasibility of the proposed modular bionic soft robot and nonlinear variable stiffness model is verified by locomotion experiments.

This paper presents a soft robot which can imitate the crawling locomotion of an earthworm. Locomotion of the robot can be achieved by expanding and contracting the body that is made of flexible material. A link of the earthworm-like robot is combined with three modules, and a multi-cavity earthworm-like soft robot is combined with multiple links. The multiple links of the earthworm-like soft robot are fabricated by silicone in the three-dimensional printed customized molds. Experiments on a single module, two-links, and three-links show that the soft robot can move and bend on condition of modules extension and contraction in a specified gait. The development of the earthworm-like soft robot shows a great prospect in many complicated environments such as pipeline detection.

When generating gaits for soft robots (those with no explicit joints), it is not evident that undulating control schemes are the most efficient. In considering alternative control schemes, however, the computational costs of evaluating continuum mechanic models of soft robots represent a significant bottleneck. We consider the use of lumped dynamic models for soft robotic systems. Such models have not been employed previously to design gaits for soft robotic systems, though they are widely used to simulate robots with compliant joints. A major question is whether these methods are accurate enough to be representations of soft robots to enable gait design and optimization. This paper addresses the potential “reality gap” between simulation and experiment for the particular case of a soft caterpillar-like robot. Experiments with a prototype soft crawler demonstrate that the lumped dynamic model can capture essential soft-robot mechanics well enough to enable gait optimization. Significantly, experiments verified that a prototype robot achieved high performance for control patterns optimized in simulation and dramatically reduced performance for gait parameters perturbed from their optimized values.